Lead AI/ML Engineer - Remote

UnitedHealth Group•Eden Prairie, MN

11h•$145,500 - $249,500•Remote

About The Position

This is a high-impact technical leadership role within the Optum Tech AI Transformation team, supporting key enterprise initiatives such as the Real-Time AI Underwriting platform. You will own the technical direction and people leadership for a squad of AI/ML engineers, driving strategic engineering efforts. Beyond building, you will lead, mentor, govern, and ensure that everything your team delivers meets the highest standards of quality, compliance, and Responsible AI. You'll serve as a bridge between engineering execution and leadership vision, ensuring AI investments translate into measurable, production-grade business outcomes. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges.

Requirements

10+ years of software development experience with a strong engineering and architecture foundation
2+ years of hands-on experience in AI/ML project implementation (full lifecycle from ideation, data analysis, model development through production deployment)
Hands-on experience with NLP (text processing, embeddings, transformers, NER, text classification, or conversational AI)
Working experience with GenAI (RAG pipelines, prompt engineering, LLM integration, fine-tuning techniques like LoRA, and enterprise deployment)
Experience or strong working knowledge of Agentic AI development (agentic workflows, tool orchestration, multi-agent systems, or planning frameworks)
Solid Python programming skills with deep proficiency in production-grade coding, code reviews, and enforcing standards
Driver’s License and access to a reliable transportation

Nice To Haves

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent professional experience)
Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, etc.) for experiment tracking, model registry, and automation
Familiarity with Responsible AI frameworks (bias detection, fairness metrics, model explainability like SHAP/LIME, and adversarial red-teaming)
Knowledge of Graph RAG, knowledge graphs, and ontology-based reasoning systems

Responsibilities

Design, develop, and deploy production-grade AI-powered solutions—spanning classical ML, Generative AI (LLMs, RAG, Graph RAG), and multi-agent orchestration frameworks—to address complex business challenges with emphasis on responsible and secure AI practices
Own the end-to-end AI/ML technical roadmap, defining architectural direction, choosing optimal technologies, and establishing engineering and coding standards for the team's portfolio
Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across the development lifecycle, optimizing team productivity and operational efficiency
Evaluate emerging trends and technologies (such as Agentic AI, foundation models, fine-tuning, and enterprise AI tooling) to inform high-quality solution design and strategic innovation
Drive MLOps maturity across development pipelines, overseeing model versioning, CI/CD for ML, retraining automation, drift detection, and production monitoring
Ensure compliance and ethical governance by aligning solutions with enterprise policies, Responsible AI principles, and data privacy regulations (HIPAA/PHI handling)
Lead, mentor, and develop a team of 5–10 direct/indirect AI/ML engineers, setting clear goals, conducting regular 1:1s, and fostering a high-performance, self-managed culture
Own and conduct robust technical reviews (architecture, design, and code reviews) to enforce rigorous standards, security posture, and pythonic best practices